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Potential Metabolite Biomarkers for Early Detection of Stage-I Pancreatic Ductal Adenocarcinoma

BACKGROUND & OBJECTIVES: Pancreatic ductal adenocarcinoma remains an extremely malignant tumor having a poor prognosis. The 5-year survival rate of PDAC is related to its stage (about 80% for stage I vs 20% for other stages). However, detection of PDAC in an early stage is difficult due to the l...

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Autores principales: Cao, Yingying, Zhao, Rui, Guo, Kai, Ren, Shuai, Zhang, Yaping, Lu, Zipeng, Tian, Lei, Li, Tao, Chen, Xiao, Wang, Zhongqiu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8807510/
https://www.ncbi.nlm.nih.gov/pubmed/35127469
http://dx.doi.org/10.3389/fonc.2021.744667
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author Cao, Yingying
Zhao, Rui
Guo, Kai
Ren, Shuai
Zhang, Yaping
Lu, Zipeng
Tian, Lei
Li, Tao
Chen, Xiao
Wang, Zhongqiu
author_facet Cao, Yingying
Zhao, Rui
Guo, Kai
Ren, Shuai
Zhang, Yaping
Lu, Zipeng
Tian, Lei
Li, Tao
Chen, Xiao
Wang, Zhongqiu
author_sort Cao, Yingying
collection PubMed
description BACKGROUND & OBJECTIVES: Pancreatic ductal adenocarcinoma remains an extremely malignant tumor having a poor prognosis. The 5-year survival rate of PDAC is related to its stage (about 80% for stage I vs 20% for other stages). However, detection of PDAC in an early stage is difficult due to the lack of effective screening methods. In this study, we aimed to construct a novel metabolic model for stage-I PDAC detection, using both serum and tissue samples. METHODS: We employed an untargeted technique, UHPLC-Q-TOF-MS, to identify the potential metabolite, and then used a targeted technique, GC-TOF-MS, to quantitatively validate. Multivariate and univariate statistics were performed to analyze the metabolomic profiles between stage-I PDAC and healthy controls, including 90 serum and 53 tissue samples. 28 patients with stage-I PDAC and 62 healthy controls were included in this study. RESULTS: A total of 10 potential metabolites presented the same expression levels both in serum and in tissue. Among them, a 2-metabolites-model (isoleucine and adrenic acid) for stage-I PDAC was constructed. The area under the curve (AUC) value was 0.93 in the discovery set and 0.90 in the independent validation set. Especially, the serum metabolite model had a better diagnostic performance than CA19-9 (AUC = 0.79). Pathway analysis revealed 11 altered pathways in both serum and tissue of stage-I PDAC. CONCLUSIONS: This study developed a novel serum metabolites model that could early separate stage-I PDAC from healthy controls.
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spelling pubmed-88075102022-02-03 Potential Metabolite Biomarkers for Early Detection of Stage-I Pancreatic Ductal Adenocarcinoma Cao, Yingying Zhao, Rui Guo, Kai Ren, Shuai Zhang, Yaping Lu, Zipeng Tian, Lei Li, Tao Chen, Xiao Wang, Zhongqiu Front Oncol Oncology BACKGROUND & OBJECTIVES: Pancreatic ductal adenocarcinoma remains an extremely malignant tumor having a poor prognosis. The 5-year survival rate of PDAC is related to its stage (about 80% for stage I vs 20% for other stages). However, detection of PDAC in an early stage is difficult due to the lack of effective screening methods. In this study, we aimed to construct a novel metabolic model for stage-I PDAC detection, using both serum and tissue samples. METHODS: We employed an untargeted technique, UHPLC-Q-TOF-MS, to identify the potential metabolite, and then used a targeted technique, GC-TOF-MS, to quantitatively validate. Multivariate and univariate statistics were performed to analyze the metabolomic profiles between stage-I PDAC and healthy controls, including 90 serum and 53 tissue samples. 28 patients with stage-I PDAC and 62 healthy controls were included in this study. RESULTS: A total of 10 potential metabolites presented the same expression levels both in serum and in tissue. Among them, a 2-metabolites-model (isoleucine and adrenic acid) for stage-I PDAC was constructed. The area under the curve (AUC) value was 0.93 in the discovery set and 0.90 in the independent validation set. Especially, the serum metabolite model had a better diagnostic performance than CA19-9 (AUC = 0.79). Pathway analysis revealed 11 altered pathways in both serum and tissue of stage-I PDAC. CONCLUSIONS: This study developed a novel serum metabolites model that could early separate stage-I PDAC from healthy controls. Frontiers Media S.A. 2022-01-19 /pmc/articles/PMC8807510/ /pubmed/35127469 http://dx.doi.org/10.3389/fonc.2021.744667 Text en Copyright © 2022 Cao, Zhao, Guo, Ren, Zhang, Lu, Tian, Li, Chen and Wang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Cao, Yingying
Zhao, Rui
Guo, Kai
Ren, Shuai
Zhang, Yaping
Lu, Zipeng
Tian, Lei
Li, Tao
Chen, Xiao
Wang, Zhongqiu
Potential Metabolite Biomarkers for Early Detection of Stage-I Pancreatic Ductal Adenocarcinoma
title Potential Metabolite Biomarkers for Early Detection of Stage-I Pancreatic Ductal Adenocarcinoma
title_full Potential Metabolite Biomarkers for Early Detection of Stage-I Pancreatic Ductal Adenocarcinoma
title_fullStr Potential Metabolite Biomarkers for Early Detection of Stage-I Pancreatic Ductal Adenocarcinoma
title_full_unstemmed Potential Metabolite Biomarkers for Early Detection of Stage-I Pancreatic Ductal Adenocarcinoma
title_short Potential Metabolite Biomarkers for Early Detection of Stage-I Pancreatic Ductal Adenocarcinoma
title_sort potential metabolite biomarkers for early detection of stage-i pancreatic ductal adenocarcinoma
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8807510/
https://www.ncbi.nlm.nih.gov/pubmed/35127469
http://dx.doi.org/10.3389/fonc.2021.744667
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